tadeephuy/CoFo
CoFo - Adversarial Contrastive Fourier Domain Adaptation (ISB I2022)
This project helps medical imaging researchers develop more accurate Computer-Aided Diagnosis (CAD) systems for colonoscopy by improving polyp segmentation. It takes diverse colonoscopy images as input and outputs precise segmentations of polyps, even when the images come from different sources or have varying visual styles. The primary users are researchers and developers working on medical image analysis and AI for healthcare.
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Use this if you are working on medical image segmentation, especially for colonoscopy polyps, and need a robust way to adapt models trained on one dataset to perform well on another without complex image translation networks.
Not ideal if you are looking for a complete, production-ready CAD system for clinical use, as this is a research implementation focused on a specific technical challenge.
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Jupyter Notebook
License
MIT
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Last pushed
Feb 15, 2022
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